Trajectory tracking control for quadrotor UAV with time-varying states constraints
Aiming at the trajectory tracking control problem of quadrotor UAV under external disturbance,model uncertainty and time-varying state constraints,a dynamic surface control scheme based on neural network is designed.Firstly,new states are obtained by nonlinear transformation of the position states,and the position states constraint problem of quadrotor UAV is transformed into a bounded problem of new states.The uncertainty in the system is estimated by neural network,then,the position and attitude dynamic surface control rates are designed respectively,and the stability is proved.Finally,simulation is conducted to compare the PD control method and the dynamic surface control method with the designed adaptive dynamic surface control method.The results validate the effectiveness and superiority of the proposed control scheme.Simulation results demonstrate that the designed control scheme ensures the stable tracking of the quadrotor UAV to the desired positional attitude with the UAV position state consistently within the desired time-varying constraints.Compared with the dynamic surface control method,the proposed control scheme exhibits a better suppression effect on external perturbation and model uncertainty.
quadrotor unmanned aerial vehicletrajectory trackingstates constraintsdynamic surface controlflight control law
NETL
NSTL
万方数据
